In this study, a NeoSpectra spectrometer was used to demonstrate the possibility of building a non-invasive blood glucose monitoring system.
PCA followed by SVM shows a promising result of 77.5%. These numerical findings reveal that the NeoSpectra spectrometer with appropriate data modeling algorithm can be a potential candidate for non-invasive blood glucose monitoring system.
M. Habibullah, M. A. M. Oninda, A. N. Bahar, A. Dinh and K. A. Wahid, "NIR-Spectroscopic Classification of Blood Glucose Level using Machine Learning Approach," 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), Edmonton, AB, Canada, 2019, pp. 1-4, doi: 10.1109/CCECE.2019.8861843.
SALES INQUIRIES + 1 650 257 9680
TECHNICAL SUPPORT + 1 844 985 4800
© 2022 Si-Ware Systems. All Rights Reserved | Terms and Conditions | Privacy Policy